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The intumescent flame retardant (IFR) technique is an alternative to halogen-based flame retardants for reducing fire hazards in polymers. However, IFR has drawbacks like unsatisfactory flame-retardant efficiency and high loading requirements. In this study, MIL-125 (Ti-based metal–organic framework) is added to ABS/IFR composites to improve flame retardancy and reduce smoke emissions. Thermogravimetric analysis (TGA) results indicate that combining ammonium polyphosphate (APP) and expandable graphite (EG) increases charred residue and slows mass loss compared with the original ABS resin. The ABS/IFR/MIL-125 system stabilizes the char layer, serving as a protective shield against combustible gases during combustion. Additionally, MIL-125 enhances performance in microscale combustion calorimetry (MCC) flammability testing. In fire tests (UL-94, limiting oxygen index (LOI), and cone calorimeter), the ABS/IFR/MIL-125 system achieves a UL-94 V0 rating and the highest LOI value of 31.5% ± 0.1%. Peak heat lease rate (PHRR) values in the cone calorimeter are reduced by 72% with 20 wt.% of additives, and smoke production decreases by 53% compared with neat ABS. These results demonstrate the efficient synergistic effects of MIL-125 and IFR additives in improving the formation and stability of the intumescent char layer, thereby protecting ABS from intense burning. [ABSTRACT FROM AUTHOR]

Ground-penetrating radar (GPR) is a well-respected, effective, and efficient geophysical technique. However, for underwater engineering detection and underwater archaeology, the measured B-scan profiles typically contain surface-related multiple waves, which can reduce the signal to noise ratio and interfere with the interpretation of results. SRME is a feedback iteration method based on wave equation, which is frequently utilized in marine seismic explorations but very rarely in GPR underwater engineering detection. To fill this gap, we applied SRME to suppress multiples that appear in GPR underwater images. When we compared the effectiveness of the underwater horizontal layered model and the underwater undulating interface model, we found a high match rate between the predicted and the real-world multiples. In addition, the addition of the Gaussian random noise level with a 4% maximum amplitude to the B-scan profile of the horizontal stratified model yielded satisfactory multiple suppression results. Finally, we applied this method to the B-scan GPR section of actual underwater archaeological images to achieve multiple suppression, which can more effectively weaken and inhibit the surface-related multiples. Both numerical simulations and actual field data show that the SRME method is highly suitable for interpreting waterborne GPR data, and more accurate interpretation can be obtained from the GPR profile after multiples suppression. [ABSTRACT FROM AUTHOR]

Traditionally, the identification and interpretation of ground-penetrating radar (GPR) images for underground pipelines have heavily relied on manual operation, which is subjective and largely dependent on the experience of operators. Conversely, the hash algorithm has been extensively researched and utilized in computer vision to classify and retrieve digital images. In this letter, we introduce a hashing-based algorithm for automatically and accurately identifying pipeline diffractions in GPR images. The pipeline identification of the GPR image is divided into two cases: single pipeline identification and multipipeline identification. In the case of single pipeline identification, we proposed an improved hash algorithm based on dc removal to improve the ability to identify hyperbolic features in GPR images. However, for multipipeline identification, we have addressed the challenge of varying grayscale changes of hyperbolic structures in GPR images caused by different materials, which may lead to inaccurate identification. To overcome this, we proposed the skeleton extraction method, which focuses solely on obtaining the shape of hyperbolic structures. By combining these methods, the fingerprints of typical pipeline images are calculated. Subsequently, the measured GPR image can be scanned using specific fingerprints in the dataset, enabling automatic and accurate pipeline identification. Experimental results have validated the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Tourmaline (TM) has received extensive interest in the purification field due to its unique spontaneous polarization. In this paper, the effects of three sizes of purified TM samples on the air filters were studied. The electrode performance of TM samples was investigated using piezoelectric and pyro‐electric experiments. The results show an electrode from the 0.074 mm separated TM had the superior property. Three types of TM powders with the highest B2O3% content were adhered to the filter to evaluate the filtration performance. Elbaite 0.074 mm with 9.34 B2O3% content had the optimal filtration efficiency when the pressure drop increased slightly. The Rietveld method was used to refine the samples X‐Ray diffraction patterns to obtain the crystal structure. The electrostatic adsorption caused by the TM spontaneous polarization contributes to improving the filtration property of the filter materials. [ABSTRACT FROM AUTHOR]